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Molecular transport across channels and pores is critically important for multiple natural and industrial processes. Recent advances in single-molecule techniques have allowed researchers to probe translocation through nanopores with unprecedented spatial and temporal resolution. However, our understanding of the mechanisms of channel-facilitated molecular transport is still not complete. We present a theoretical approach that investigates the role of molecular interactions in the transport through channels. It is based on the discrete-state stochastic analysis that provides a fully analytical description of this complex process. It is found that a spatial distribution of the interactions strongly influences the translocation dynamics. We predict that there is the optimal distribution that leads to the maximal flux through the channel. It is also argued that the channel transport depends on the strength of the molecule-pore interactions, on the shape of interaction potentials and on the relative contributions of entrance and diffusion processes in the system. These observations are discussed using simple physical-chemical arguments.

The structural properties and thermal stability of dipalmitoylphosphatidylethanolamine (DPPE) in the ordered gel phase have been studied by molecular dynamics simulation using two force fields: the Berger united-atom model and the CHARMM C36 atomistic model. As is widely known, structural features are sensitive to the initial preparation of the gel phase structure, as some degrees of freedom are slow to equilibrate on the simulation time scale of hundreds of nanoseconds. In particular, we find that the degree of alignment of the lipids' glycerol backbones, which join the two hydrocarbon tails of each molecule, strongly affects the tilt angle of the tails in the resulting structures. Disorder in the backbone correlates with lower tilt angles: bilayer configurations initiated with aligned backbones produced tilt angles near 21° and 29° for the Berger and C36 force fields, respectively, while structures initiated with randomized backbone orientations showed average tilt angles of 7° and 18°, in closer agreement with the untilted structure observed experimentally. The transition temperature for the Berger force field gel bilayer has been determined by monitoring changes in width of gel phase stripe domains as a function of temperature and is 12 ± 5 K lower than the experimental value.

Respiratory syncytial virus (RSV) is a common virus that can have varying effects ranging from mild cold-like symptoms to mortality depending on the age and immune status of the individual. We combined mathematical modelling using ordinary differential equations (ODEs) with measurement of RSV infection kinetics in primary well-differentiated human bronchial epithelial cultures in vitro and in immunocompetent and immunosuppressed cotton rats to glean mechanistic details that underlie RSV infection kinetics in the lung. Quantitative analysis of viral titre kinetics in our mathematical model showed that the elimination of infected cells by the adaptive immune response generates unique RSV titre kinetic features including a faster timescale of viral titre clearance than viral production, and a monotonic decrease in the peak RSV titre with decreasing inoculum dose. Parameter estimation in the ODE model using a nonlinear mixed effects approach revealed a very low rate (average single-cell lifetime > 10 days) of cell lysis by RSV before the adaptive immune response is initiated. Our model predicted negligible changes in the RSV titre kinetics at early times post-infection (less than 5 dpi) but a slower decay in RSV titre in immunosuppressed cotton rats compared to that in non-suppressed cotton rats at later times (greater than 5 dpi) in silico. These predictions were in excellent agreement with the experimental results. Our combined approach quantified the importance of the adaptive immune response in suppressing RSV infection in cotton rats, which could be useful in testing RSV vaccine candidates.

Intracellular transport is a fundamental biological process during which cellular materials are driven by enzymatic molecules called motor proteins. Recent optical trapping experiments and theoretical analysis have uncovered many features of cargo transport by multiple kinesin motor protein molecules under applied loads. These studies suggest that kinesins cooperate negatively under typical transport conditions, although some productive cooperation could be achieved under higher applied loads. However, the microscopic origins of this complex behavior are still not well understood. Using a discrete-state stochastic approach we analyze factors that affect the cooperativity among kinesin motors during cargo transport. Kinesin cooperation is shown to be largely unaffected by the structural and mechanical parameters of a multiple motor complex connected to a cargo, but much more sensitive to biochemical parameters affecting motor-filament affinities. While such behavior suggests the net negative cooperative responses of kinesins will persist across a relatively wide range of cargo types, it is also shown that the rates with which cargo velocities relax in time upon force perturbations are influenced by structural factors that affect the free energies of and load distributions within a multiple kinesin complex. The implications of these later results on transport phenomena where loads change temporally, as in the case of bidirectional transport, are discussed.

Proton cancer therapy (PCT) utilizes high-energy proton projectiles to obliterate cancerous tumors with low damage to healthy tissues and without the side effects of X-ray therapy. The healing action of the protons results from their damage on cancerous cell DNA. Despite established clinical use, the chemical mechanisms of PCT reactions at the molecular level remain elusive. This situation prevents a rational design of PCT that can maximize its therapeutic power and minimize its side effects. The incomplete characterization of PCT reactions is partially due to the health risks associated with experimental/clinical techniques applied to human subjects. To overcome this situation, we are conducting time-dependent and non-adiabatic computer simulations of PCT reactions with the electron nuclear dynamics (END) method. Herein, we present a review of our previous and new END research on three fundamental types of PCT reactions: water radiolysis reactions, proton-induced DNA damage and electron-induced DNA damage. These studies are performed on the computational prototypes: proton + H2O clusters, proton + DNA/RNA bases and + cytosine nucleotide, and electron + cytosine nucleotide + H2O. These simulations provide chemical mechanisms and dynamical properties of the selected PCT reactions in comparison with available experimental and alternative computational results.

Intracellular transport is supported by enzymes called motor proteins that are often coupled to the same cargo and function collectively. Recent experiments and theoretical advances have been able to explain certain behaviors of multiple motor systems by elucidating how unequal load sharing between coupled motors changes how they bind, step, and detach. However, non-mechanical interactions are typically overlooked despite several studies suggesting that microtubule-bound kinesins interact locally via short-range non-mechanical potentials. This work develops a new stochastic model to explore how these types of interactions influence multiple kinesin functions in addition to mechanical coupling. Non-mechanical interactions are assumed to affect kinesin mechanochemistry only when the motors are separated by less than three microtubule lattice sites, and it is shown that relatively weak interaction energies (~2 kBT) can have an appreciable influence over collective motor velocities and detachment rates. In agreement with optical trapping experiments on structurally-defined kinesin complexes, the model predicts that these effects primarily occur when cargos are transported against loads exceeding single-kinesin stalling forces. Overall, these results highlight the inter-dependent nature of factors influencing collective motor functions, namely, that the way the bound configuration of a multiple motor system evolves under load determines how local non-mechanical interactions influence motor cooperation.

Subcellular cargos are often transported by teams of processive molecular motors, which raises questions regarding the role of motor cooperation in intracellular transport. Although our ability to characterize the transport behaviors of multiple-motor systems has improved substantially, many aspects of multiple-motor dynamics are poorly understood. This work describes a transition rate model that predicts the load-dependent transport behaviors of multiple-motor complexes from detailed measurements of a single motor's elastic and mechanochemical properties. Transition rates are parameterized via analyses of single-motor stepping behaviors, load-rate-dependent motor-filament detachment kinetics, and strain-induced stiffening of motor-cargo linkages. The model reproduces key signatures found in optical trapping studies of structurally defined complexes composed of two kinesin motors, and predicts that multiple kinesins generally have difficulties in cooperating together. Although such behavior is influenced by the spatiotemporal dependence of the applied load, it appears to be directly linked to the efficiency of kinesin's stepping mechanism, and other types of less efficient and weaker processive motors are predicted to cooperate more productively. Thus, the mechanochemical efficiencies of different motor types may determine how effectively they cooperate together, and hence how motor copy number contributes to the regulation of cargo motion.

Although the motions of many sub-cellular cargos are known to be driven by teams of microtubule motor proteins, understanding the role collective motor function plays in intracellular transport has been difficult to characterize. One confounding issue is that a team of molecular motors can adopt a spectrum of microtubule-associated configurations, depending on the number of bound motors and their organization on the microtubule. Since each microstate configuration can confer different mechanical and dynamic properties to a cargo, understanding how molecular motors function collectively ultimately requires knowledge of their relative contribution to cargo motility. To address this issue, we have developed methods to examine the load-dependent transport properties of structurally-defined multiple motor systems composed of two kinesin-1 molecules. Herein, we describe a discrete microstate transition-rate model of two-kinesin mechanics that can explain several unexpected behaviors observed in our assays. While this model accounts for a comprehensive spectrum of geometric arrangements of motors between a cargo and the microtubule, transition rates between microstate configurations are almost exclusively parameterized using data from single-kinesin optical trapping measurements. Overall, our model shows strong agreement with our data and recapitulates the central experimental finding that configurations where two kinesins both assume a portion of the applied load are rare and short-lived, causing two kinesins to exhibit negative cooperativity and properties that resemble the action of a single motor molecule. The bottom-up construction of our model also allows us to explore the effects of changes in single motor properties such as compliance, force-velocity relationship, and forward/backward stepping behavior on the dynamics of the system as a whole. This now provides a foundation for analyses of transport behaviors produced by more complex systems composed of different numbers, types and geometric arrangements of motors.

The motion of molecules across channels and pores is critically important for understanding mechanisms of many cellular processes. Here we investigate the mechanism of interactions in the molecular transport through nanopores by analyzing exactly solvable discrete stochastic models. According to this approach the channel transport is viewed as a set of chemical transitions between discrete states. It is shown that the strength and spatial distribution of molecule/channel interactions can strongly modify the particle current. Our analysis indicates that the most optimal transport is achieved when the binding sites are near the entrance or exit of the pore depending on the sign of interaction potential. In addition, the role of intermolecular interactions during the channel transport is studied, and it is argued that an increase in the flux can be observed for some optimal interaction strength. The mechanisms of these phenomena are discussed.